One of the biggest challenges to determining fluid mobility in rock samples is the very fine microstructure in some rock samples—like shale. Shale significantly differs from all other formation rocks in the grain size, which corresponds to very low values for porosity (Φ) and permeability (k).
Conventional techniques for determining fluid mobility in rock samples include:                Nuclear Magnetic Resonance (NMR);        3D CT scanning, that enables contouring density differences i.e. contrast in the scanned image;        X-ray diffraction; and        SEM evaluation of rock samples.        
One of the main disadvantages is that such conventional techniques can only operate with and handle very small rock samples referred to as core plugs, which are not representative of the entire sample—much less the reservoir. In other words, the fluid mobility determined by such conventional techniques is not representative of the in-situ fluid mobility and thus, must be adjusted for a more accurate representation. The determination of fluid mobility by any of the foregoing conventional techniques may be improved by “upscaling,” which extrapolates petrophysical properties from the core-plug scale to determine the simulation-grid scale. Many upscaling techniques are well known and available such as, for example, power-law average, renormalization, pressure-solver, tensor and pseudofunction techniques. In short, upscaling replaces a number of heterogeneous fine grid blocks with one equivalent coarse homogeneous grid block. The essence of conventional upscaling requires averaging and extrapolation, which therefore, leads to the loss of information and creates the common problem of blurring the spatially continuous extremes such as, for example, shale barriers and open fractures. Oil and gas recovery mainly depends on the spatial connectivity of the extreme (ultra-low) permeability values, particularly characteristic of small scale shale pores. Determining fluid mobility in rock samples without upscaling is therefore, preferred.
Other conventional techniques for determining fluid mobility in rock samples include: i) grinding the rock samples; ii) removing all of the water content from the rock samples; and iii) injecting He or Hg into the rock samples. These techniques, however, are not optimal because they skew the original geo-mechanical properties of the rock sample before determining fluid mobility and may still require upscaling for very small rock samples (core plugs).
As a result, applications of positron radiation detection have emerged from more traditional medical imaging applications using Positron Emission Tomography (“PET”). In standard PET imaging, data acquired in two-dimensional (2D) or three-dimensional (3D) form are stored in sinograms that consist of rows and columns representing angular and radial samplings, respectively. The raw data are pre-binned by the hardware into the sinogram format. Due to the pre-binning operation, the data in the sinogram format result in lower resolution from the original raw data, which results in the loss of valuable information about the scanned object. In sinogram format, the acquired data in each row are compressed (summed) along the depth of the object and must be decompressed to provide information along this direction. In Nonmedical Applications of a Positron Camera, Nuclear Instruments and Methods in Physics Research A310, 1991, pp. 423-434, written by Hawkesworth, et al., for example, PET is used to produce images every ten (10) minutes to track fluid flow in rock samples. This technology, however, is limited because the acquired data is stored in sinograms, which require more time to process than the original raw data stored in list mode. As a result, the image rate is slow (1 every 10 minutes), which lowers the image resolution.
In Porosity and Pathway Determination in Crystalline Rock by Positron Emission Tomography and Neutron Radiography, Earth and Planetary Science Letters 140, 1996, pp. 213-225, written by Degueldre, et al., the fluid pathway and porosity in crystalline rock samples have been studied with a high-resolution PET camera. The results demonstrate original water carrier features in granodiorite pieces 20 cm in size and in simulated features with porosities on the order of 20%. In Positron Emission Tomography of Large Rock Samples Using a Multiring PET Instrument, IEEE Transactions on Nuclear Science, Vol. 44, No. 1, 1997, pp. 26-30, written by Maguire, et al., the use of PET has been extended to a multi-ring PET camera and demonstrates that the measurements of porosity in large rock samples (21.5 cm) are indeed practicable using 3D acquisition techniques. These techniques, however, are limited to images of just the rock sample structure and therefore, do not illustrate dynamic fluid mobility within the rock sample structure. These techniques also suffer the same shortcomings as other techniques that store acquired data in the sinogram format.
Present research by the University of Cape Town in South Africa utilizes time-lapse PEPT, tags sub-20 μm rock particles and liquids with tags (tracers) having activities of ˜100 μCi to determine the mobility of a rock particle in a slurry and a liquid in a column of glass beads. Here, the activity of the tag refers to the radioactive decay in which an unstable (i.e. (radio)active) atomic nucleus looses energy by emitting one or more ionizing particles (i.e. ionizing energy). In PEPT applications, the (radio)active tag emits positrons. Because the acquired data is stored in list mode, the images may be produced at a rate of more than one image per second. As a result, fluid mobility may be determined more accurately because the image quality is improved. This research, however, has not been applied to determine fluid mobility in rock samples, particularly rock samples with small scale pores (less than μD) like shale, because the tag used for the particles is too large for accurate determination of fluid (gas and liquid) mobility.